DocumentCode :
468140
Title :
An Efficient Method for Attribute Reduction in Incomplete Information Systems
Author :
Li, Renpu ; Zhao, Yongsheng ; Zhang, Fuzeng ; Song, Lihua
Author_Institution :
Ludong Univ., Yantai
Volume :
1
fYear :
2007
fDate :
24-27 Aug. 2007
Firstpage :
352
Lastpage :
356
Abstract :
Attribute reduction is an important issue of data mining. In this paper a novel method based on rough sets is provided for attribute reduction in incomplete information systems. Through a transformation technique, an incomplete system is firstly converted into a new and simpler system and then reducts are obtained from the transformed system. It is proved by theorem that the transformed system has the same reducts as the previous one. Experiments show that the proposed method is more efficient on reduct computation of incomplete information systems.
Keywords :
data mining; rough set theory; attribute reduction; data mining; incomplete information systems; rough sets; transformed system; Computer science; Data mining; Information systems; Machine learning; Rough sets; Set theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
Type :
conf
DOI :
10.1109/FSKD.2007.152
Filename :
4405946
Link To Document :
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